Investigation on the statistical methods in research studies of library and information science
Abstract
Purpose The statistical method plays an extremely important role in quantitative research studies in library and information science (LIS). The purpose of this paper is to investigate the status of statistical methods used in the field, their application areas and the temporal change patterns during a recent 15-year period. Design/methodology/approach The research papers in six major scholarly journals from 1999 to 2013 in LIS were examined. Factors including statistical methods, application areas and time period were analyzed using quantitative research methods including content analysis and temporal analysis methods. Findings The research studies using statistical methods in LIS have increased steadily. Statistical methods were more frequently used to solve problems in the information retrieval area than in other areas, and inferential statistical methods were used more often than predictive statistical methods and other statistical methods. Anomaly analysis on statistical method uses was conducted and four types of anomaly were specified. Originality/value The findings of this study can help educators, graduates and researchers in the field of LIS better understand the patterns and trends of the applications of statistical methods in this field, depict an overall picture of quantitative research studies in LIS from the perspective of statistical methods and discover the change patterns of statistical method applications in LIS between 1999 and 2013.
Integrity signals
Registry
Cites
Statistics
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Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The use of inferential statistics in the library science literature is increasing.
“Given the continued pressure on libraries to quantitavely demonstrate their value and contribution to students' learning outcomes, and the increasing use of inferential statistics in the library science literature (Wallace 1985; Zhang, Wang, and Zhao 2017; Zhang et al. 2018)”
From Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies (2019) · cites this paper as Zhang, Wang, and Zhao 2017
Cited by
Sorted by citations
Unethical Numbers? A Meta-analysis of Library Learning Analytics Studies
Robertshaw, M. B., & Asher, A. (2019) · Library Trends · doi:10.1353/lib.2019.0031 · Cited by 32 · see citing works
- Authors
- Zhang, J., Wang, Y., & Zhao, Y.
- Affiliations
- University of Wisconsin–Milwaukee (US)
- Venue
- The Electronic Library
- Publisher
- Emerald
- Published
- 2017-11-06
- Volume
- 35
- Issue
- 6
- Pages
- 1070-1086
- ISSN
- 0264-0473 (ISSN-L)
- OpenAlex
- W2766009490
- Cited by
- 12
- References
- 0
- Citations by year
- 2026: 1 · 2025: 1 · 2022: 3 · 2021: 2 · 2020: 1 · 2019: 2 · 2018: 2
- FWCI
- 1.23
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- The Electronic Library (publishedVersion)
- Topics
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › scientometrics and bibliometrics research
- Physical Sciences › Computer Science › Information Systems › Library Science and Information
- Social Sciences › Library and Information Sciences › Library Science and Information Literacy
- Keywords
- statistical analysis, library and information science research, quantitative research, information retrieval, statistical inference, temporal trends, anomaly analysis, research methodology use
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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